Multi-objective evolutionary algorithm for grid job scheduling based on adaptive neighborhood

Abstract

A new adaptive neighborhood Multi-Objective Grid Task Scheduling Algorithm(ANMO-GTSA) was proposed in this paper for the multi-objective job scheduling collaborative optimization problem in grid computing.In the ANMO-GTSA,an adaptive neighborhood method was applied to find the non-inferior set of solutions and maintain the diversity of the multi-objective job scheduling population.The experimental results indicate that the algorithm proposed in this paper can not only balance the multi-objective job scheduling,but also improve the resource utilization and efficiency of task execution.Moreover,the proposed algorithm can achieve better performance on time-dimension and cost-dimension than the traditional Min-min and Max-min algorithms.